Decision Tree-Supported Analysis of Gallium Arsenide Growth Using the LEC Method

0579923 - ÚI 2024 RIV CH eng J - Journal Article
Tang, X. - Chappa, G. K. - Viera, L. - Holeňa, Martin - Dropka, N.
Decision Tree-Supported Analysis of Gallium Arsenide Growth Using the LEC Method.
Crystals. Roč. 13, č. 12 (2023), s. 1659. ISSN 2073-4352. E-ISSN 2073-4352
Institutional support: RVO:67985807
Keywords : LEC growth * gallium arsenide * CFD * regression tree
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Impact factor: 2.7, year: 2022
Method of publishing: Open access
https://doi.org/10.3390/cryst13121659

In this study, an axisymmetric Czochralski furnace model for the LEC growth of gallium arsenide is presented. We produced 88 datasets through computational fluid dynamics simulations. Among the many parameters that affect crystal growth, a total of 13 input parameters were selected, including the geometry and material parameters of the hot zone (crucible, heaters, radiation shield, and crystal), as well as the process parameters (such as pulling and rotation rates, heating power, etc.). Voronkov criteria (v/Gn), interface deflection, and the average interface temperature gradient were selected as the output parameters. We carried out a correlation analysis between the variables and used decision trees to study the impact of the 13 input variables on the output variables. The results indicated that in the growth of gallium arsenide, the main factor affecting interface deflection and the average interface thermal gradients is the crucible rotation rate. For v/Gn, it is the pulling rate.
Permanent Link: https://hdl.handle.net/11104/0348712